Understanding and Mitigating Hazards

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Fire sign
Fire sign
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This research has developed a prototype, high-resolution soil-moisture analysis system called JASMIN, which is a significant improvement in accuracy compared to currently used models. It is based on research that examines the use of land surface models, remotely sensed satellite measurements and data assimilation techniques to improve the monitoring and prediction of soil dryness. The new information will be calibrated for use within the existing fire prediction systems. This retains the accuracy, temporal and spatial resolution of the new product without changing the overall climatology of Forest Fire Danger Index and other calculations based on soil moisture.

Good estimates of landscape dryness underpin fire danger ratings, fire behaviour models, and flood prediction. Soil dryness also strongly influences heatwave development by driving the transfer of solar heating from the soil surface into air temperature rise.

Fire intensity, spread rate and ignition are sensitive to the fuel dryness, which is strongly linked to soil moisture content. Estimates and forecasts of fuel dryness and soil moisture are the foundation of the fire danger calculations used to rate and manage bushfires and to warn of developing fire danger. Similarly, estimates and forecasts of soil moisture are essential ingredients to be able to forecast with accuracy river flows on a seasonal scale (one to three months), which is much in demand by water managers and reservoir operators.

This research has developed a prototype, high-resolution soil-moisture analysis system called JASMIN, which is a significant improvement in accuracy compared to currently used models. It is based on research that examines the use of land surface models, remotely sensed satellite measurements and data assimilation techniques to improve the monitoring and prediction of soil dryness. The new information will be calibrated for use within the existing fire prediction systems. This retains the accuracy, temporal and spatial resolution of the new product without changing the overall climatology of Forest Fire Danger Index and other calculations based on soil moisture.

A pilot project is being initiated, where rescaled outputs from routine JASMIN runs with daily updates will be published in registered user webpages for fire agencies to assess. The routine updates will also be disseminated to the Bureau of Meteorology’s extreme weather desk, where the severe weather forecasters can assess the product using the forecasting tools (for example, the Bureau of Meteorology’s Visual Weather product) available to them. Also, fire agencies using Visual Weather will be able to use the outputs directly.

A case study of the State Mine fire in the Blue Mountains in October 2013, compared JASMIN with the traditionally used Keetch-Byram Drought Index. JASMIN is far drier compared to KBDI, which may be under-predicting the soil dryness, as verifications have shown that it generally has a large wet-bias.

Immediate benefits for emergency and land management agencies will be improvements to the fire danger rating and warning system, fire behaviour and flood prediction models, which will flow on to emergency warnings issued to the public. The project’s long-term goal is to integrate JASMIN’s outputs into the new National Fire Danger Rating System.

Post fire field work
19 December, 2016
New journal articles and reports on CRC research are available online.
Year Type Citation
2017 Journal Article Kumar, V. et al. Comparison of soil wetness from multiple models over Australia with observations. Water Resources Research 53, 633-646 (2017).
2016 Conference Paper Rumsewicz, M. Research proceedings from the 2016 Bushfire and Natural Hazards CRC and AFAC conference. Bushfire and Natural Hazards CRC & AFAC annual conference 2016 (Bushfire and Natural Hazards CRC, 2016).
2016 Conference Paper Dharssi, I. & Kumar, V. A high-resolution land dryness analysis system for Australia. AFAC16 (Bushfire and Natural Hazards CRC, 2016).
2016 Journal Article Holgate, C. M. et al. Comparison of remotely sensed and modelled soil moisture data sets across Australia. Remote Sensing of Environment 186, (2016).
2016 Report Dharssi, I. & Kumar, V. Mitigating the effects of severe fires, floods and heatwaves through the improvements of land dryness measures and forecasts: Annual project report 2015-2016. (Bushfire and Natural Hazards CRC, 2016).
2015 Conference Paper Rumsewicz, M. Research proceedings from the 2015 Bushfire and Natural Hazards CRC & AFAC conference. Bushfire and Natural Hazards CRC & AFAC annual conference 2015 (Bushfire and Natural Hazards CRC, 2015).
2015 Conference Paper Dharssi, I., Kumar, V., Yeo, C., Bally, J. & Kepert, J. D. Mitigating the Effects of Severe Fires, Floods and Heatwaves Conference Paper 2014. Bushfire and Natural Hazards CRC and AFAC Wellington Conference 2014 (2015).
2015 Presentation Dharssi, I. & Kumar, V. Mitigating the effects of severe fires, floods and heatwaves through the improvements of land dryness measures and forecasts. (2015).
2015 Report Dharssi, I. & Kumar, V. Mitigating the effects of severe fires, floods and heatwaves through improvements to land dryness measures and forecasts: Annual project report 2014-2015. (Bushfire and Natural Hazards CRC, 2015).
2015 Report Dharssi, I. Mitigating the Effects of Severe Fires, Floods and Heatwaves Annual Report 2014. (2015).
Mitigating the effects of severe fires, floods and heatwaves through the improvements of land dryness measures and forecasts
25 Aug 2014

This project will improve Australia’s ability to manage extreme events by developing a state of the art, world’s best practice in soil moisture analysis.

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Sources of Soil Dryness Measures and Forecasts
18 Aug 2015

Emerging new approaches to evaluate landscape dryness through the use of satellite remote sensing data, land surface modelling and data assimilation techniques are available, measuring dryness more systematically than the empirical methods. Satellite measurements can be blended with land surface model simulations to provide more accurate, detailed and confident estimates and forecasts of land dryness.

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Vinod Kumar Conference Poster 2016
14 Aug 2016

Soil dryness is a key component in operational fire danger rating systems.

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Improved measures and forecasts of soil dryness
29 Jun 2017

New approaches are available to calculate soil dryness more accurately through the use of satellite remote sensing measurements, land surface modelling and data analysis techniques.

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